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Code4lib is hiring: Data Access Librarian in Baltimore

Code4lib
Baltimore, MD Full Time
POSTED ON 3/25/2025 CLOSED ON 4/16/2025

What are the responsibilities and job description for the Code4lib is hiring: Data Access Librarian in Baltimore position at Code4lib?

We are seeking a Data Access Librarian who will be responsible for the selection, discovery, and access of institutional, open-access, community, and purchased datasets serving Johns Hopkins researchers, faculty, students, and staff. As a member of the Digital Scholarship & Data Services team, the data access librarian promotes data literacy and the discovery and use of relevant datasets through providing individual consultations and developing and delivering workshops, training programs, and research guides. The data access librarian supports and collaborates with colleagues in data services, Academic Liaisons, Hopkins researchers and faculty, the larger academic data librarian and data services community, and especially the new Data Science and AI Institute at Johns Hopkins University.

Specific Duties & Responsibilities

  • Conducts consultations and answers patron inquiries related to secondary data, particularly on discovering, accessing, evaluating, and working with datasets.
  • In collaboration with Technical Services and the Discovery and Access team, selects, describes, and promotes discovery and access to datasets provided through Data Services, open-access and community repositories, and purchased from vendors.
  • Develops and delivers instructional programming, including workshops and classroom sessions on finding, evaluating, and using secondary data of all types and on tools and methods to effectively work with data.
  • Conducts outreach and builds relationships with researchers, faculty, and students on their needs around data discovery and access.
  • Serves as the Organization Representative to the Inter-University Consortium for Political and Social Research (ICPSR).
  • Acquires and licenses datasets and related resources for the library’s collection in coordination with relevant colleagues and stakeholders.
  • Administers the Johns Hopkins Libraries Data Grant data purchase program.
  • Represents Data Services on the JHU Sheridan Libraries Social Sciences Collection team.
  • Prepares secondary datasets and their metadata for improved access and discovery.
  • Creates and maintains relevant library guides and other informational resources for users.
  • Reports to library and university leadership on dataset usage and needs.
  • Performs other duties as assigned.

Special Knowledge, Skills, & Abilities

  • Thorough understanding of the tools and methods for finding and assessing datasets relevant to specific research needs, the academic research process, and data literacy in higher education.
  • Strong understanding of the methods and data requirements of research in Artificial Intelligence.
  • Knowledge of programmatic tools and technologies for data access including API use in languages like R and Python, SQL, and some familiarity with data cleaning, normalization, and visualization.
  • Ability to work independently and to collaborate with diverse colleagues and patrons.
  • Ability to learn and apply new skills and evidence of ongoing self-directed learning.
  • Commitment to promoting diversity, equity, and inclusion.
  • Minimum Qualifications

  • MLS from an ALA-accredited library school or an advanced related degree.
  • Three years professional library experience.
  • Preferred Qualifications

  • Experience with medium-to-large data sets (over 1 million rows).
  • Experience providing instruction, consultation, and public services in a library or academic setting, preferably including via video conferencing.
  • Experience with collection development, acquisitions, and licensing of library resources.
  • Technical Qualifications or Specialized Certifications

  • Skill in using tools and technologies for data access, data cleaning, normalization, and visualization, including SQL, R, and Python.
  • How to apply

    Apply here

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